Yun Liu
I am a professor at the College of Computer Science, Nankai University.
Previously, I served as a senior scientist at the Institute for Infocomm Research (I2R), A*STAR.
Prior to that, I was a postdoctoral researcher in the Computer Vision Lab at ETH Zurich,
working under the supervision of Prof. Luc Van Gool.
I obtained both my bachelor's and doctoral degrees from Nankai University in 2016 and 2020, respectively,
under the guidance of Prof. Ming-Ming Cheng.
My research interests focus on computer vision and deep learning.
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Selected Publications
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Exploring Frequency-Inspired Optimization in Transformer for Efficient Single Image Super-Resolution
Ao Li, Le Zhang, Yun Liu, and Ce Zhu
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025
[PDF] [Code] [Official Version] -
Learning Local and Global Temporal Contexts for Video Semantic Segmentation
Guolei Sun, Yun Liu*, Henghui Ding, Min Wu, and Luc Van Gool
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024
[PDF] [Code] [Official Version] -
PSRR-MaxpoolNMS++: Fast Non-Maximum Suppression with Discretization and Pooling
Tianyi Zhang, Chunyun Chen, Yun Liu*, Xue Geng, Mohamed M. Sabry Aly, and Jie Lin
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024
[PDF] [Official Version] -
Rethinking Few-shot 3D Point Cloud Semantic Segmentation
Zhaochong An, Guolei Sun*, Yun Liu*, Fayao Liu, Zongwei Wu, Dan Wang, Luc Van Gool, and Serge Belongie
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024
[PDF] [Code] [Official Version] -
Vision Transformers with Hierarchical Attention
(First titled "Transformer in Convolutional Neural Networks")
Yun Liu, Yu-Huan Wu, Guolei Sun, Le Zhang, Ajad Chhatkuli, and Luc Van Gool
Machine Intelligence Research (MIR), 2024
[PDF] [Code] [Official Version] -
Rethinking Global Context in Crowd Counting
(First titled "Boosting Crowd Counting with Transformers")
Guolei Sun, Yun Liu*, Thomas Probst, Danda Pani Paudel, Nikola Popovic, and Luc Van Gool
Machine Intelligence Research (MIR), 2024
[PDF] [Official Version] -
Towards Open-Vocabulary Video Semantic Segmentation
Xinhao Li, Yun Liu, Guolei Sun, Min Wu, Le Zhang, and Ce Zhu
IEEE Transactions on Multimedia (TMM), 2024
[PDF] [Code] [Official Version] -
Revisiting Computer-Aided Tuberculosis Diagnosis
Yun Liu, Yu-Huan Wu, Shi-Chen Zhang, Li Liu, Min Wu, and Ming-Ming Cheng
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
[PDF] [Project Page] [Code] [Dataset on Google Drive] [Dataset on Baidu Yunpan] [中译版] [Online Challenge] [Official Version] -
Feature Modulation Transformer: Cross-Refinement of Global Representation via High-Frequency Prior for Image Super-Resolution
Ao Li, Le Zhang, Yun Liu, and Ce Zhu
International Conference on Computer Vision (ICCV), 2023
[PDF] [Supplementary Material] [Code] [Official Version] -
Indiscernible Object Counting in Underwater Scenes
Guolei Sun, Zhaochong An, Yun Liu, Ce Liu, Christos Sakaridis, Deng-Ping Fan, and Luc Van Gool
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
[PDF] [Supplementary Material] [Code] [Official Version] -
Boosting Salient Object Detection with Transformer-based Asymmetric Bilateral U-Net
Yu Qiu, Yun Liu*, Le Zhang, and Jing Xu*
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2023
[PDF] [Code] [Official Version] -
Mining Relations among Cross-Frame Affinities for Video Semantic Segmentation
Guolei Sun, Yun Liu*, Hao Tang, Ajad Chhatkuli, Le Zhang, and Luc Van Gool
European Conference on Computer Vision (ECCV), 2022
[PDF] [Code] [Official Version] -
Coarse-to-Fine Feature Mining for Video Semantic Segmentation
Guolei Sun, Yun Liu*, Henghui Ding, Thomas Probst, and Luc Van Gool
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
[PDF] [Code] [Official Version] -
P2T: Pyramid Pooling Transformer for Scene Understanding
Yu-Huan Wu#, Yun Liu#, Xin Zhan, and Ming-Ming Cheng
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
[PDF] [Code] [中译版] [Official Version] -
EDN: Salient Object Detection via Extremely-Downsampled Network
Yu-Huan Wu#, Yun Liu#, Le Zhang, Ming-Ming Cheng, and Bo Ren
IEEE Transactions on Image Processing (TIP), 2022
[PDF] [Code] [Official Version] -
MiniSeg: An Extremely Minimum Network Based on Lightweight Multiscale Learning for Efficient COVID-19 Segmentation
Yu Qiu, Yun Liu*, Shijie Li, and Jing Xu*
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
[PDF] [Code] [Official Version] -
A2SPPNet: Attentive Atrous Spatial Pyramid Pooling Network for Salient Object Detection
Yu Qiu, Yun Liu*, Yanan Chen, Jianwen Zhang, Jinchao Zhu, and Jing Xu*
IEEE Transactions on Multimedia (TMM), 2022
[PDF] [Official Version] -
Zero Pixel Directional Boundary by Vector Transform
Edoardo Mello Rella, Ajad Chhatkuli, Yun Liu, Ender Konukoglu, and Luc Van Gool
International Conference on Learning Representations (ICLR), 2022
[PDF] [Official Version] -
Semantic Edge Detection with Diverse Deep Supervision
Yun Liu, Ming-Ming Cheng, Deng-Ping Fan, Le Zhang, Jia-Wang Bian, and Dacheng Tao
International Journal of Computer Vision (IJCV), 2021
[PDF] [Code] [中译版] [Official Version] -
SAMNet: Stereoscopically Attentive Multi-scale Network for Lightweight Salient Object Detection
Yun Liu#, Xin-Yu Zhang#, Jia-Wang Bian, Le Zhang, and Ming-Ming Cheng
IEEE Transactions on Image Processing (TIP), 2021
[PDF] [Code] [中译版] [Official Version] -
DNA: Deeply-supervised Nonlinear Aggregation for Salient Object Detection
Yun Liu, Ming-Ming Cheng, Xin-Yu Zhang, Guang-Yu Nie, and Meng Wang
IEEE Transactions on Cybernetics (TCYB), 2021
[PDF] [Saliency Maps] [中译版] [Official Version] -
MiniSeg: An Extremely Minimum Network for Efficient COVID-19 Segmentation
Yu Qiu, Yun Liu*, Shijie Li, and Jing Xu*
AAAI Conference on Artificial Intelligence (AAAI), 2021
[PDF] [Code] [Official Version] -
MobileSal: Extremely Efficient RGB-D Salient Object Detection
Yu-Huan Wu, Yun Liu, Jun Xu, Jia-Wang Bian, Yuchao Gu, and Ming-Ming Cheng
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
[PDF] [Project Page] [Code] [Official Version] -
DOTS: Decoupling Operation and Topology in Differentiable Architecture Search
Yuchao Gu, Lijuan Wang, Yun Liu, Yi Yang, Yu-Huan Wu, Shao-Ping Lu, and Ming-Ming Cheng
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
[PDF] [Supplementary Material] [Code] [Official Version] -
Leveraging Instance-, Image- and Dataset-Level Information for Weakly Supervised Instance Segmentation
Yun Liu#, Yu-Huan Wu#, Peisong Wen, Yujun Shi, Yu Qiu, and Ming-Ming Cheng
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
[PDF] [Code] [中译版] [Official Version] -
Rethinking Computer-aided Tuberculosis Diagnosis
Yun Liu#, Yu-Huan Wu#, Yunfeng Ban, Huifang Wang, and Ming-Ming Cheng
IEEE Conference on Computer Vision and Pattern Recognition (CVPR, Oral), 2020
[PDF] [Project Page] [Dataset on Google Drive] [Dataset on Baidu Yunpan] [Online Challenge] [中译版] [Video] [PPT] [Official Version] -
Lightweight Salient Object Detection via Hierarchical Visual Perception Learning
Yun Liu#, Yu-Chao Gu#, Xin-Yu Zhang#, Weiwei Wang, and Ming-Ming Cheng
IEEE Transactions on Cybernetics (TCYB), 2020
[PDF] [Code] [中译版] [Official Version] -
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation
Shijie Li, Yazan Abu Farha, Yun Liu, Ming-Ming Cheng, and Juergen Gall
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
[PDF] [Project Page] [Code] [Official Version] -
Ordered or Orderless: A Revisit for Video based Person Re-Identification
Le Zhang, Zenglin Shi, Joey Tianyi Zhou, Ming-Ming Cheng, Yun Liu, Jia-Wang Bian, Zeng Zeng, and Chunhua Shen
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
[PDF] [Code] [Official Version] -
GMS: Grid-based Motion Statistics for Fast, Ultra-robust Feature Correspondence
Jia-Wang Bian, Wen-Yan Lin, Yun Liu, Le Zhang, Sai-Kit Yeung, Ming-Ming Cheng, and Ian Reid
International Journal of Computer Vision (IJCV), 2020
[PDF] [Project Page] [Code] [Video] [Official Version] -
Pyramid Constrained Self-Attention Network for Fast Video Salient Object Detection
Yuchao Gu, Lijuan Wang, Ziqin Wang, Yun Liu, Ming-Ming Cheng, and Shao-Ping Lu
AAAI Conference on Artificial Intelligence (AAAI), 2020
[PDF] [Project Page] [Code] [Official Version] -
RefinedBox: Refining for Fewer and High-quality Object Proposals
Yun Liu, Shi-Jie Li, and Ming-Ming Cheng
Neurocomputing, 2020
[PDF] [Code] [中译版] [Official Version] -
Richer Convolutional Features for Edge Detection
Yun Liu, Ming-Ming Cheng, Xiaowei Hu, Jia-Wang Bian, Le Zhang, Xiang Bai, and Jinhui Tang
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019
[PDF] [Project Page] [Code] [Official Version] -
Nonlinear Regression via Deep Negative Correlation Learning
Le Zhang, Zenglin Shi, Ming-Ming Cheng, Yun Liu, Jia-Wang Bian, Joey Tianyi Zhou, Guoyan Zheng, and Zeng Zeng
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019
[PDF] [Project Page] [Code] [Official Version] -
Scoot: A Perceptual Metric for Facial Sketches
Deng-Ping Fan, ShengChuan Zhang, Yu-Huan Wu, Yun Liu, Ming-Ming Cheng, Bo Ren, Paul Rosin, and Rongrong Ji
International Conference on Computer Vision (ICCV), 2019
[PDF] [Project Page] [Supplementary Material] [Code] [Official Version] -
Multi-Level Context Ultra-Aggregation for Stereo Matching
Guang-Yu Nie, Ming-Ming Cheng, Yun Liu, Zhengfa Liang, Deng-Ping Fan, Yue Liu, and Yongtian Wang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
[PDF] [Project Page] [Supplementary Material] [PPT] [Official Version] -
BING: Binarized Normed Gradients for Objectness Estimation at 300fps
Ming-Ming Cheng#, Yun Liu#, Wen-Yan Lin, Ziming Zhang, Paul L. Rosin, and Philip Torr
Computational Visual Media (CVMJ), 2019
[PDF] [Project Page] [Code] [Official Version] -
DEL: Deep Embedding Learning for Efficient Image Segmentation
Yun Liu, Peng-Tao Jiang, Vahan Petrosyan, Shi-Jie Li, Jiawang Bian, Le Zhang, and Ming-Ming Cheng
International Joint Conference on Artificial Intelligence (IJCAI), 2018
[PDF] [Project Page] [Code] [中译版] [Official Version] -
Crowd Counting with Deep Negative Correlation Learning
Zenglin Shi, Le Zhang, Yun Liu, XiaoFeng Cao, Yangdong Ye, Ming-Ming Cheng, and Guoyan Zheng
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018
[PDF] [Project Page] [Code] [Official Version] -
Sequential Optimization for Efficient High-Quality Object Proposal Generation
Ziming Zhang, Yun Liu, Xi Chen, Yanjun Zhu, Ming-Ming Cheng, Venkatesh Saligrama, and Philip H.S. Torr
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017
[PDF] [Code] [Official Version] -
Structure-measure: A New Way to Evaluate Foreground Maps
DengPing Fan, Ming-Ming Cheng, Yun Liu, Tao Li, and Ali Borji
International Conference on Computer Vision (ICCV, Spotlight), 2017
[PDF] [Project Page] [Code] [PPT] [Official Version] -
Richer Convolutional Features for Edge Detection
Yun Liu, Ming-Ming Cheng, Xiaowei Hu, Kai Wang, and Xiang Bai
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
[PDF] [Project Page] [Code] [中译版] [Official Version] -
HFS: Hierarchical Feature Selection for Efficient Image Segmentation
Ming-Ming Cheng#, Yun Liu#, Qibin Hou, Jiawang Bian, Philip Torr, Shi-Min Hu, and Zhuowen Tu
European Conference on Computer Vision (ECCV), 2016
[PDF] [Project Page] [Code] [中译版] [Official Version]